A Deep Graph-based Toolbox for Fraud Detection
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Updated
Apr 20, 2022 - Python
A Deep Graph-based Toolbox for Fraud Detection
A collection of GNN-based fake news detection models.
EquiDock: geometric deep learning for fast rigid 3D protein-protein docking
Knowledge-Aware Graph Networks for Commonsense Reasoning (EMNLP-IJCNLP 19)
Code for CIKM 2020 paper Enhancing Graph Neural Network-based Fraud Detectors against Camouflaged Fraudsters
Enterprise graph machine learning framework for billion-scale graphs for ML scientists and data scientists.
FUNDED is a novel learning framework for building vulnerability detection models.
A Deep Graph-based Toolbox for Fraud Detection in TensorFlow 2.X
Graph Convolutional Networks for 4-class EEG Classification
Artifact for OSDI'21 GNNAdvisor: An Adaptive and Efficient Runtime System for GNN Acceleration on GPUs.
Learning Fraud Detection from research papers and industry applications.
Bayesian Graph Neural Networks with Adaptive Connection Sampling - Pytorch
Code for reproducing results in GraphMix paper
WWW2020-One2Multi Graph Autoencoder for Multi-view Graph Clustering
Tracking and Trajectory Prediction
Code for our paper: Scalable Multi-Agent Reinforcement Learning through Intelligent Information Aggregation
Graph Neural Network architecture to solve the decision version of the graph coloring problem (GCP)
This repository contains a dataset for testing graph classification algorithms, such as Graph Kernels and Graph Neural Networks.
Pytorch implementation of "Large-Scale Representation Learning on Graphs via Bootstrapping"
Supporting code for doi 10.1021/acs.jcim.0c01344
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